Exploring Data in Virtual Reality: Comparisons with 2D Data Visualizations

Patrick Millais; Simon Jones; Ryan Kelly

doi:10.1145/3170427.3188537

Exploring Data in Virtual Reality: Comparisons with 2D Data Visualizations

Patrick Millais, Simon Jones, Ryan Kelly

Department of Computer Science

University of Melbourne

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

70 Citations (SciVal)

577 Downloads (Pure)

Abstract

Virtual Reality (VR) has often been discussed as a promising medium for immersive data visualization and exploration. However, few studies have evaluated users’ open-ended exploration of multi-dimensional datasets using VR and compared the results with that of traditional (2D) visualizations. Using a workload- and insight-based evaluation methodology, we conducted a user study to perform such a comparison. We find that there is no overall task-workload di↵erence between traditional visualizations and visualizations in VR, but there are di↵erences in the accuracy and depth of insights that users gain. Our results also suggest that users feel more satisfied and successful when using VR data exploration tools, thus demonstrating the potential of VR as an engaging medium for visual data analytics.

Original language	English
Title of host publication	CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems
Publisher	Association for Computing Machinery
Volume	2018-April
ISBN (Electronic)	9781450356206, 9781450356213
DOIs	https://doi.org/10.1145/3170427.3188537
Publication status	Published - 21 Apr 2018

Keywords

Data Dashboards
Data Visualization
Virtual Reality

ASJC Scopus subject areas

Human-Computer Interaction
Computer Graphics and Computer-Aided Design
Software

Access to Document

10.1145/3170427.3188537

paper1278
(C) ACM, 2018. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in CHI'18 Extended Abstracts, April 21 - 26, 2018, http://doi.acm/org/10.1145/3170427.3188537.
Accepted author manuscript, 3.66 MBLicence: Unspecified

Cite this

Exploring Data in Virtual Reality: Comparisons with 2D Data Visualizations. / Millais, Patrick; Jones, Simon; Kelly, Ryan.
CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems. Vol. 2018-April Association for Computing Machinery, 2018. LBW007.

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

@inproceedings{f4706343186c48f2be81255ad127e06d,

title = "Exploring Data in Virtual Reality: Comparisons with 2D Data Visualizations",

abstract = "Virtual Reality (VR) has often been discussed as a promising medium for immersive data visualization and exploration. However, few studies have evaluated users{\textquoteright} open-ended exploration of multi-dimensional datasets using VR and compared the results with that of traditional (2D) visualizations. Using a workload- and insight-based evaluation methodology, we conducted a user study to perform such a comparison. We find that there is no overall task-workload di↵erence between traditional visualizations and visualizations in VR, but there are di↵erences in the accuracy and depth of insights that users gain. Our results also suggest that users feel more satisfied and successful when using VR data exploration tools, thus demonstrating the potential of VR as an engaging medium for visual data analytics.",

keywords = "Data Dashboards, Data Visualization, Virtual Reality",

author = "Patrick Millais and Simon Jones and Ryan Kelly",

year = "2018",

month = apr,

day = "21",

doi = "10.1145/3170427.3188537",

language = "English",

volume = "2018-April",

booktitle = "CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems",

publisher = "Association for Computing Machinery",

address = "USA United States",

}

TY - GEN

T1 - Exploring Data in Virtual Reality: Comparisons with 2D Data Visualizations

AU - Millais, Patrick

AU - Jones, Simon

AU - Kelly, Ryan

PY - 2018/4/21

Y1 - 2018/4/21

N2 - Virtual Reality (VR) has often been discussed as a promising medium for immersive data visualization and exploration. However, few studies have evaluated users’ open-ended exploration of multi-dimensional datasets using VR and compared the results with that of traditional (2D) visualizations. Using a workload- and insight-based evaluation methodology, we conducted a user study to perform such a comparison. We find that there is no overall task-workload di↵erence between traditional visualizations and visualizations in VR, but there are di↵erences in the accuracy and depth of insights that users gain. Our results also suggest that users feel more satisfied and successful when using VR data exploration tools, thus demonstrating the potential of VR as an engaging medium for visual data analytics.

AB - Virtual Reality (VR) has often been discussed as a promising medium for immersive data visualization and exploration. However, few studies have evaluated users’ open-ended exploration of multi-dimensional datasets using VR and compared the results with that of traditional (2D) visualizations. Using a workload- and insight-based evaluation methodology, we conducted a user study to perform such a comparison. We find that there is no overall task-workload di↵erence between traditional visualizations and visualizations in VR, but there are di↵erences in the accuracy and depth of insights that users gain. Our results also suggest that users feel more satisfied and successful when using VR data exploration tools, thus demonstrating the potential of VR as an engaging medium for visual data analytics.

KW - Data Dashboards

KW - Data Visualization

KW - Virtual Reality

UR - http://www.scopus.com/inward/record.url?scp=85052027134&partnerID=8YFLogxK

U2 - 10.1145/3170427.3188537

DO - 10.1145/3170427.3188537

M3 - Chapter in a published conference proceeding

VL - 2018-April

BT - CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems

PB - Association for Computing Machinery

ER -

Exploring Data in Virtual Reality: Comparisons with 2D Data Visualizations

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

The Language of Collaborative Manufacture

Cite this

Exploring Data in Virtual Reality: Comparisons with 2D Data Visualizations

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Projects

The Language of Collaborative Manufacture

Cite this